Dr. Cynthia Rudin – The Champion of Transparent AI

• Professor, Duke University
• Focus: Interpretable machine learning
• Ethos: High-stakes decisions deserve clarity—not black boxes.

Rudin has long advocated for “white-box” AI models, especially in healthcare, criminal justice, and energy. Her work is instrumental in designing models that are both accurate and understandable, making AI more trustworthy and democratic. She was awarded the 2022 AAAI Squirrel AI Award—often called the “Nobel Prize of AI for social good.”

Dr.Timnit Gebru – Ethics with Backbone

• Founder, Distributed AI Research Institute (DAIR)
• Focus: Ethical AI, large language models, bias in data
• Ethos: Ethical resistance is not optional—it’s essential.

Gebru co-authored the landmark paper “On the Dangers of Stochastic Parrots,” igniting debate over the unchecked growth of LLMs. Her departure from Google sparked global conversation on tech ethics and diversity. A co-founder of Black in AI, Timnit remains a moral force in AI, advocating for transparency, inclusion, and accountability.

Dr. Joelle Pineau – A Force for Open Science

• VP of AI Research at Meta | Professor, McGill University
• Focus: Reinforcement learning, reproducibility in AI
• Ethos: Reproducibility is the cornerstone of trustworthy science.

Pineau is a key figure in developing reproducible AI benchmarks and methods. Her work has made AI research more transparent and collaborative. At Meta, she leads groundbreaking work in healthcare and embodied AI. Her academic rigor and open science advocacy have raised the field’s standards.

Dr. Joy Buolamwini – The Conscience of AI

• Founder, Algorithmic Justice League | MIT Media Lab Alumna
• Focus: Facial recognition bias, algorithmic justice
• Ethos: Tech should serve all of humanity—not just a privileged few.

Joy’s groundbreaking research exposed racial and gender bias in commercial facial recognition systems. Her viral TED Talk, “How I’m fighting bias in algorithms”, helped push Amazon, IBM, and Microsoft to pause or reevaluate their facial recognition tech. A poet of code, Joy fuses art and activism to create technologies that reflect justice and inclusion.

Dr. Nuria Oliver – Data for Humanity

• Co-founder, ELLIS Alicante (Spain) | Former Scientific Director, Telefónica
• Focus: Mobile data, human behavior modeling
• Ethos: Data science should serve the public good.

Oliver helped lead Spain’s COVID-19 data response, using AI to model pandemic behavior. Her AI-driven projects in public health and urban planning are models for responsible, impactful tech.

Dr. Hongxia Yang – Big Data, Bigger Vision

• Professor, Hong Kong Polytechnic University (formerly Alibaba & ByteDance)
• Focus: Recommender systems, generative AI
• Ethos: Industry and academia must collaborate to build practical AI.

After leading AI research at Alibaba and TikTok, Hongxia moved to academia to focus on democratizing AI development. Her work powers large-scale AI systems across billions of users and continues to influence commercial and academic AI.

Dr. Francesca Rossi – Diplomat of AI Ethics

• IBM Fellow, Global Leader in AI Ethics
• Focus: Constraint reasoning, value-aligned AI
• Ethos: AI should be aligned with our deepest human values.

Rossi has worked tirelessly to incorporate ethics into AI development. She serves on advisory boards for the UN, EU, and IEEE, helping shape global AI governance. At IBM, she ensures that AI systems are not just intelligent—but responsible.

Karen Hao – The Storyteller of the AI Revolution

• Journalist & Award-Winning AI Reporter
• Former Roles: Senior Editor at MIT Technology Review, China Tech Correspondent at The Wall Street Journal
• Focus: AI ethics, policy, geopolitics, and accountability
• Ethos: The public deserves to understand AI—not just its promises, but its perils.

Karen Hao has carved a unique niche in the AI ecosystem—not by building models but by breaking stories. Through meticulous reporting, she’s demystified the power structures, ethical failures, and systemic biases embedded in the AI industry. Her MIT Technology Review series on Facebook’s AI ethics struggles was one of the first to connect the dots between corporate ambition and global harm. 

Dr. Ayanna Howard – Humanizing the Machine

• Dean, College of Engineering at Ohio State University
• Focus: Robotics, assistive AI
• Ethos: Inclusive tech is good tech.

From working on NASA’s Mars rovers to building robots that assist children with disabilities, Howard blends compassion with innovation. She’s also a leading voice on algorithmic bias and the importance of diversity in AI development and education.

Dr. Abeba Birhane – Decolonizing AI

• Senior Fellow, Mozilla Foundation | Adjunct Lecturer, Trinity College Dublin
• Focus: Data justice, algorithmic bias
• Ethos: Technology must respect human dignity and cultural context.

Birhane’s research challenges Western-centric, dehumanizing AI data practices. Her work prompted the removal of racist and inappropriate images from widely-used datasets. She champions African perspectives and cognitive science in shaping AI ethics.

Dr. Virginia Dignum – Architect of Responsible AI

• Professor, Umeå University (Sweden)
• Focus: AI governance, ethics frameworks
• Ethos: AI should be built with—not for—society.

Dignum has helped craft global AI ethics guidelines and consults with the UN, OECD, and EU. Her policy work is grounded in deep technical understanding and a passion for participatory technology.

Dr. Pascale Fung – Voice of Compassionate Machines

• Professor, HKUST | Director, Centre for AI Research
• Focus: Conversational AI, empathy in machines
• Ethos: Machines must understand emotions to truly serve humans.

Fung was among the first to build multilingual, empathetic AI dialogue systems. She combines technical excellence with strong advocacy for ethical AI, especially in Asia-Pacific.

Dr. Ayesha Khanna – Smart Cities, Smarter Societies

• CEO, ADDO AI (Singapore)
• Focus: AI strategy, education, fintech
• Ethos: The future must be inclusive, data-driven, and female-led.

Through her firm ADDO AI, Khanna leads smart city AI solutions across Asia and Africa. She also founded 21C Girls, empowering young women in STEM through AI education.

Dr. Geetha Manjunath – Saving Lives with AI

• CEO & Founder, Niramai (India)
• Focus: AI in healthcare diagnostics
• Ethos: Privacy and accessibility must guide healthtech.

Manjunath developed a low-cost, AI-driven breast cancer screening tool using thermal imaging—particularly transformative in low-resource settings. Her solution is non-invasive, portable, and now deployed across dozens of hospitals in India.

Dr. Adji Bousso Dieng – Africa’s AI Luminary

• Assistant Professor, Princeton University
• Focus: Probabilistic models, scientific discovery
• Ethos: AI should uplift underrepresented communities.

The first Black woman faculty member in Princeton CS, Dieng also founded The Africa I Know to celebrate African excellence in STEM. Her work bridges deep learning and global equity.

Dr. Dena Al Mansoori – AI Architect of the Gulf

• Chief AI & Data Officer, e& (Etisalat Group, UAE)
• Focus: AI strategy, telecom, HR tech
• Ethos: Leadership must scale innovation with inclusion.

Al Mansoori leads AI initiatives across 38 countries for Etisalat, one of the world’s largest telecom firms. A serial innovator, she champions women in tech and ethical AI use in the enterprise.

Dr. Suchi Saria – Predictive Precision for Patients

• Professor, Johns Hopkins | CEO, Bayesian Health
• Focus: AI in clinical decision-making
• Ethos: AI should anticipate illness—not just react to it.

Her machine learning tools for predicting sepsis and other complications are now used in major hospitals. With Bayesian Health, she’s translating academic research into tools that improve patient outcomes in real-time.

Dr. Fei-Fei Li – AI’s North Star

• Professor, Stanford University | Co-Director, HAI
• Focus: Computer vision, human-centered AI
• Ethos: AI must reflect the full spectrum of humanity.

Fei-Fei co-created ImageNet and laid the foundation for modern computer vision. Today, she champions AI that augments—not replaces—human potential. Her leadership is shaping national AI policy and public understanding.

Dr. Marzyeh Ghassemi – Machine Learning with Empathy

• Professor, MIT (EECS & IMES)
• Focus: Interpretable ML, healthcare equity
• Ethos: Models trained on bias deepen injustice—they must be audited.

Ghassemi’s research focuses on fairness and interpretability in medical data. Her interdisciplinary work ensures that AI doesn’t exacerbate disparities in care but instead helps close health gaps.

Dr. Olga Russakovsky 

– The Equity Engineer

• Assistant Professor, Princeton University
• Focus: Computer vision, AI fairness
• Ethos: Representation in AI starts with who builds it.

A co-developer of ImageNet, Russakovsky also co-founded AI4ALL, a nonprofit training underrepresented high school students in AI. She advocates for inclusive datasets and diversity in AI pipelines.

Dr. Jennifer Vaughan  – Responsible Research at Scale

• Principal Researcher, Microsoft Research | Affiliate, University of Washington
• Focus: Algorithmic fairness, responsible AI practices
• Ethos: AI tools must reflect collective care, not just technical prowess.

Vaughan co-founded the FAccT conference and helps create industry-leading frameworks for documenting AI systems. Her work ensures that responsible AI isn’t an afterthought—it’s a foundation.